Method of determining a battery solution for a vehicle

ABSTRACT

A module-based framework evaluates designs of advanced start stop systems, particularly 12V advanced start stop systems. The framework separates vehicle and battery analysis and uses a power profile to evaluate different designs of the vehicles and batteries. Particularly, the framework can evaluate different battery solutions and compare performances as a function of drive cycles, motor size, and electrical loads. In addition to modeling, actual batteries are tested for the same power inputs for validating performance differences. This framework identifies performance limiting components for determination of the vehicle system component optimization.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims priority to U.S. Provisional Patent ApplicationNo. 62/580,745 filed Nov. 2, 2017 the entirety of which is incorporatedherein by reference.

FIELD

Battery performance varies by the particular demands that a vehicleplaces on it causing different battery performance characteristicsassociated to different vehicles. Determining optimal batteryperformance, or optimal battery solution, for a given vehicle, or classof vehicles, becomes complicated with the numerous types andapplications of power demands for those vehicles. Modeling designprocesses have advanced in sophistication in attempting to replicateactual vehicle environments for battery usage, but generally fail toprovide sufficient equivalence. Addressing this lack of equivalence, amethodology facilitating an accelerated design process of integratingbatteries to vehicles is provided based on (1) separating vehiclesimulation and battery modeling and (2) combining vehicle and batteryparameters within an integration platform. In particular, a modularizedvehicle simulation tool implements a 12V advanced start-stop vehiclebattery solution.

BACKGROUND OF THE INVENTION

The advantages of vehicle electrification of 12V automotive systems isappealing to automotive manufacturers. Although fuel economies of 12Velectrification are generally not directly applicable to 48V and highvoltage hybrid automotive systems, total fuel savings are potentiallysignificant based on the large quantity of conventional vehiclescurrently in use today. Standardization of 12V electrification solutionsremains problematic as designs are dependent on both vehicle and batteryvariables. As such a singular battery solution for all, or most,vehicles does not appear to solve this problem.

To address this need, a module-based simulation tool builds batteryparameters based on vehicle demands together with component selectionbased on control optimization. A model framework includes the connectionof different modules and data flows between the different modules.

SUMMARY OF THE INVENTION

A module-based framework evaluates designs of advanced start stopsystems, particularly 12V advanced start stop systems. The frameworkseparates vehicle and battery analysis and uses a power profile toevaluate different designs of the vehicles and batteries. Particularly,the framework can evaluate different battery solutions and compareperformances as a function of drive cycles, motor size, and electricalloads. In addition to modeling, actual batteries are tested for the samepower inputs for validating performance differences. This frameworkidentifies performance limiting components for determination of thevehicle system component optimization.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a module-based simulation tool for 12V advanced startstop system design.

FIG. 2 illustrates a Matlab/Simulink interface of the battery simulationmodule. This module accepts inputs of vehicle status and power requestand outputs the current, voltage, SOC for performance evaluation.

FIG. 3 shows the Autonomie software interface showing where parametersare modified to simulate a particular vehicle.

FIG. 4 is a graphical representation of driving profile (WLTP) and powerprofile. The top graphical representation illustrates the vehiclevelocity profile; the middle illustrates the regen power profilegenerated by Autonomic simulation for VW Golf without electrical loadsand cranking; and the bottom illustrates modified power profile byadding constant load of 400 W and cranking pulse.

FIG. 5 is a graphical representation of the results of current, power,and voltage profiles respectively for simulation.

FIG. 6 is a graphical representation of showing the charge acceptanceand fuel economy as a function of motor size for different batterysolutions based on WLTP driving profiles. The top graphicalrepresentation illustrates charge acceptance and the bottom illustratesfuel economy.

FIG. 7 is a graphical representation of simulations of FIG. 6 performedwith conditions of 800 W load. The top graphical representationillustrates charge acceptance and the bottom illustrates fuel economy.

FIG. 8 is a graphical representation of how changing driving cycle toNEDC affects the performance of different battery solutions having 400 Welectrical loads. The top graphical representation illustrates chargeacceptance and the bottom illustrates fuel economy.

FIG. 9 is a graphical representation of how changing driving cycle toNEDC affects the performance of different battery solutions have 800 Welectrical loads. The top graphical representation illustrates chargeacceptance and the bottom illustrates fuel economy.

FIG. 10 is a graphical representation showing simulation results basedon US CAFÉ standard (55% FTP72+45% HWFET) for 400 W electrical loads.The to graphical representation illustrates charge acceptance and thebottom illustrates fuel economy.

FIG. 11 is a graphical representation showing simulation results basedon US CAFÉ standard (55% FTP72+45% HWFET) for 800 W electrical loads.The top graphical representation illustrates charge acceptance and thebottom illustrates fuel economy.

DETAILED DESCRIPTION OF THE INVENTION

Referring to the module-based simulation tool for 12V advanced startstop system design of FIG. 1, in the part of vehicle simulation an“infinite” battery (very big capacity and very small resistance) is usedto remove any power limit from the battery. In terms of a 12V advancedstart-stop vehicle, the motor size limits how much free energy thevehicle can get and is a key parameter to choose. Also the electricalloads and its management are key parameters which depends on batterystatus and have strong effects on performance. In the second module ofbattery simulation, the battery control strategy and battery model areincluded. The battery control strategy defines conditions for which thebattery will be charged and supports the needed loads. The battery modelvaries by energy storage solution to be selected.

Additionally, FIG. 2 shows the Matlab/Simulink outline of the batterysimulation module. The third part involves the calculation of a few keyperformance like peak power which determines battery size, SOC swing (Ahthroughput) which relates to battery life, and fuel economy which is thebenefit the end users will get. As shown in FIG. 2, this module acceptsinputs of vehicle status and power request and outputs the current,voltage, SOC for performance evaluation.

In principal, all the parts of simulation and calculations in FIG. 1 canbe done is a single simulation environment (model). However, separatingthe vehicle simulation and battery simulation facilitates the designiterations. For example, an OEM asks battery suppliers to come up withsuggestions for battery solutions (chemistry and size) for a particularvehicle, which includes the power requests as to a particularperformance scenario or numerous critical performance scenarios) ofinterest to the OEM. Different battery suppliers will use the same powerprofiles to evaluate their solutions and feed back to the OEM regardingthe performance. In another example once the battery is selected, theOEM may desire electrical loads to be transferred to the battery insteadof using traditional alternator and optimize the loads management. Inthis situation the OEM may desire that the battery supplier providetheir battery model and focus on investigation of electrical loadsmanagements and calibrating the battery charging/discharging strategy.The Simulink interface shown in FIG. 2 shows how the battery moduleworks. The battery module accepts power requests and vehicle status andoutputs the simulated current, voltage, and SOC for performancecharacterization module.

Battery solution evaluations for 12V advanced start stop vehicles are aparticular case. To demonstrate the functions of module-based simulationtool previously described, the simulation of a few battery solutions fora given power profile and compare the performance in terms of fueleconomy and charge acceptance is provided.

Vehicle Selection and Parameters

An Autonomie 2015 version as the simulation tool and simulated a 2017Volkswagen Golf was used. The parameters are listed in Table 1 which iscollected from public sources. FIG. 3 shows the software interfacedemonstrating where the parameters are modified to reflect a particularvehicle. Note that we have used an “infinite” battery during simulationand the electrical loads was set to zero.

TABLE 1 Vehicle parameters of 2017 VW Golf Weight (lbs) 3023 Dragcoefficient 0.29 Front area (m²) 2.59 Engine power (hp) 170 Tire radius(m) 0.31 Final drive 3.87 Gear ratio (6 levels) 4.46-0.67 Motor power(kW) 1-6FIG. 3: the Autonomie software interface showing where parameters aremodified to simulate a particular vehicle.Four driving profiles were simulated: NEDC, WLTP, FTP72, and HWFET.Table 2, below, shows the characteristics of the four driving profiles.Of note was that the sum of idle time and regen energy vary with drivingcycles which affect the fuel economy. Also the available regen energyvaries with motor size.

TABLE 2 Driving cycle characteristics WLTP NEDC FTP72 HWFET Duration(s)1800 1180 1369 764 Distance(km) 23.07 10.99 11.84 16.50 Number of 8 1316 1 stops Idle time(s) 206 240 207 0 Total regen energy(Wh) Motor = 1kW 68.2 32.4 45.5 12.7 Motor = 2 kW 122.6 61.4 84.5 23.1 Motor = 3 kW168.8 87.0 116.3 31.3 Motor = 4 kW 209.3 108.4 144.6 38.0 Motor = 5 kW244.7 123.4 169.7 44.0 Motor = 6 kW 274.7 135.8 191.3 49.4

As an example, a simulated power profile (WLTP and motor power=3 kW) isshown in FIG. 4 where the top one shows vehicle speed profile (WLTP). Asshown in FIG. 4, driving profile (WLTP) and power profile with (top) thevehicle velocity profile, (middle) regen power profile generated byAutonomie simulation for VW Golf without electrical loads and crankingand (bottom) modified power profile by adding constant load of 400 W andcranking pulse. The middle figure shows vehicle simulated power profilewhich only contains the regen profile since electrical load is set tozero. The bottom figure in FIG. 4 shows modified power profile withadding a constant electrical load of 400 W and cranking pulse. Thebottom profile will feed to battery simulation for battery evaluations.

Considerations of battery solutions selection and parameters wereexemplified considering a variety of battery solutions for 12V advancedstart stop vehicles currently in use. The comparison of three solutionsincluded:

1) Stand-alone AGM H6 (70 Ah)

2) Dual batteries of AGM H6 (70 Ah) and LTO (10 Ah) that are passivelyparallelized.

3) Stand-alone LFP (69 Ah)

For all batteries involved (four chemistries) an equivalent circuitmodel (RRC) was used. To obtain model parameters, HPPC tests areperformed and then model parameters are obtained by fitting as functionof temperature and SOC. Although limited to room temperature performanceother variables are contemplated, and other model parameters may bedistinct. Tests on battery batteries (cells) are representative of themodel provided, and other distinct results may result from a product.For each battery solution some mechanical resistance was added toreflect different architectures of battery solutions listed in Table 3.

For battery control strategy, specifically the charging strategy, theoperating SOC (or voltage) need to be defined which varies withchemistry. Table 3 also includes the variables related to controlstrategy. For lead acid, the target SOC is 80% and for LFP it is 90%SOC. With dual batteries it is voltage controlled and set at 13V.

TABLE 3 Battery mechanical resistance and control variables. VariablesAGM H6 Dual LFP Mechanical resistance (mΩ) 0 LTO: 1.0  0.5 AGM: 2.0 Topvoltage (V) 14.8 14.8 14.8 Target SOC 80% ′/ 90% Operating voltage (V) /13 /

Performance characterization may utilize a method of charge acceptanceand fuel economy to characterize performance of each battery solution.For charge acceptance a total accepted charge may be used, such as(integral of charging current) divided by driving cycle time as acriteria.

For 12V advanced start stop, vehicle fuel economy is improved by startstop function and regen function. To estimate the fuel economy firstlythe fuel saved by start stop function is calculated by equation 1,below.

$\begin{matrix}{{G\; P\; M_{{s\alpha ved}\_{SS}}} = \frac{f_{idle}{D\left( {t_{stop} - {10{s \cdot \left( {n - 1} \right)}}} \right)}}{d}} & (1)\end{matrix}$

Where f_(idle) is the fuel consumption when engine is at idle statewhich is set as 2.51×10⁻⁵ gal/s/L.

D is the engine size (1.8 L). t_(stop) is the vehicle stop time inseconds and n is the number of starts.

d is the driving distance in mile.

Then to estimate the fuel saved by regen function, the motor energywhich is used to support electrical load is calculated by equation 2,below.

$\begin{matrix}{E_{Motor} = {\int_{0}^{\Delta\; t}{\left( {{{Load}(W)} + {P_{bat}(t)}} \right){dt}}}} & (2)\end{matrix}$P_(bat)(t) is the battery power. It is negative when it discharges(supporting loads) and positive when it is charged (motor chargesbattery and supports loads). Note that equation 1 is only valid when thebattery initial SOC is equal to end or final SOC. During batterysimulation we have tuned initial SOC to achieve neutrality so that wecan use the above equation to estimate fuel economy. Then the saved gas,GPM_(saved_Regen), is calculated by equation 3, below.

$\begin{matrix}{{G\; P\; M_{{saved}\_{Regen}}} = \frac{{{{Load}(W)}*\Delta\; t} - E_{Motor}}{\rho_{gas} \cdot \eta \cdot d}} & (3)\end{matrix}$

Where ρ_(gas)=3.4×10⁴ Wh/Gal, is the energy density of gas, η is theenergy conversion efficiency from gas to electricity, which is assumedto be 27%. And d (miles) is the vehicle traveled distance for drivingprofile. From equation 3 one can see that the saved gas is limited byaccessory loads. After GPM_(saved_SS) and GPM_(saved_Regen) are obtainedby equation 1 and 3, we use the following equation to calculate mile pergallon with advanced start stop function, MPG_(new).

$\begin{matrix}{{M\; P\; G_{new}} = \frac{1}{{G\; P\; M_{baseline}} - {GPM_{{saved}\_{SS}}} - {GPM_{{saved}\_{Regen}}}}} & (4)\end{matrix}$In which GPM_(baseline) is the gallon per mile for vehicle withoutadvanced start stop function which equals 1/MPG_(baseline). We have usedMPG_(baseline)=25 for city and MPG_(baseline)=35 for highway. Finallythe fuel economy (FE) is calculated by comparing MPG_(new) andMPG_(baseline).

The simulation results of two typical cases are presented below:

A) Driving cycle=WLTP, Motor=3 kW, AGM H6

B) Driving cycle=WLTP, Motor=3 kW, Dual batteries of AGM H6 and NMC/LTO.

As seen in FIG. 5 (from top to bottom) the results of current, power,and voltage profiles are provided. The current and power profiles ofFIG. 5 show that the dual battery solution has much higher chargeacceptance as demonstrated by higher currents (power) during braking andsupports longer the loads during stop. The reason is that the dualsolution has much lower charge resistance as demonstrated by the voltageprofile where dual battery solution has much smaller voltage swing. Acharge neutral was kept so that the fuel economy calculated by equations1-4 has a fair comparison.

FIG. 6 shows the charge acceptance and fuel economy as a function ofmotor size for different battery solutions based on WLTP drivingprofiles. Note that the ideal case is also presented in FIG. 6 where theideal means a constant voltage (set as 13V) battery with zeroresistance. The ideal battery represents the best performance the systemcan get based on the inputs of vehicle setup except the battery. FIG. 6shows that both charge acceptance and fuel economy increases with motorsize due to increase of available regen energy from the motor. However,all of them reach a certain limit. AGM H6 reaches a 3.7% fuel economylimit starting from 3 kW. The other three systems reach 5% fuel economystarting from 4 kW. The reasons are however different. For lead acid itis the charge resistance that limits its performance as FIG. 5 hasshown. At 3 kW the battery has reaches top voltage and not able toaccept higher regen power. However for the other three systems, theelectrical load of 400 W is limiting and not the battery resistance.Note that we have performed charge neutral simulations to get the truefuel economy. The vehicle can provide more regen and battery can acceptmore regen. However, due to limitation of usage, there is not more fueleconomy benefit.

To verify electrical load is limiting the performance, the samesimulations are performed with conditions of 800 W load. The chargeacceptance and fuel economy results are presented in FIG. 7. As can beseen, the three systems (Dual, LFP, Ideal) all have no limitationsanymore and fuel economy increases to as high as 6%. However, the leadacid is still limited by its poor charge acceptance (high chargeresistance).

FIGS. 8 and 9 shows how changing driving cycle to NEDC affects theperformance of different battery solutions. Simulations in FIG. 8 has400 W electrical loads and simulations of FIG. 9 has 800 W. Comparingwith WLTP systems one can see that:

-   -   1) For different battery solutions NEDC shows similar trends as        WLTP, however it has higher fuel economy due to longer stop        time.    -   2) Increasing the load from 400 W to 800 W does not cause much        change in both fuel economy and charge acceptance because NEDC        has less regen than WLTP and then electrical load is not a        limiting factor anymore.

FIGS. 10 and 11 show the simulation results based on US CAFE standard(55% FTP72+45% HWFET) for 400 W and 800 W respectively. The US CAFEresults are similar with WLTP results. At high motor size theperformance is somewhat limited by electrical loads.

Table 4, below, summarizes the fuel economy benefit for differentbattery solutions depending on driving cycles and electrical loads. Astart-stop baseline is also presented. The baseline only reflects enginestop at rest and does not include regen braking. As seen in Table 4:

-   -   1) A simple start stop application without regen certainly        limits the AGM capability to achieve higher fuel economy.    -   2) There is a gap between lead acid and lithium ion solution due        to lower charge acceptance of AGM. However, when the electrical        load are small, the gap between AGM and lithium ion solution are        small.

TABLE 4 Fuel economy comparison of different battery solutions. SSOptimal FE baseline AGM Dual LFP Ideal WLTP 400 W 1.1% 3.7% 4.8% 5.0%5.0% 800 W 3.6% 5.9% 6.0% 6.6% NEDC 400 W 2 0% 4.7% 7.2% 7.4% 7.6% 800 W4.7% 7.4% 7.5% 7.8% US 400 W 0.6% 3.1% 4.8% 4.8% 4.9% CAFE 800 W 3.1%5.3% 5.4% 5.9%

The 12V advanced start stop systems can offer 5-8% fuel economyimprovement over a conventional vehicle. Although the fuel economy isnot as high as those of mild to full hybrids, its low implementationcost makes it an attractive electrification solutions for vehicles. As aresult, the 12V advanced start stop technology has been evolving fast inrecent years.

On one hand, battery suppliers are offering a variety of energy storagesolutions such as stand-alone lead acid, stand-alone LFP/Graphite, dualbatteries of lead acid parallel with NMC/LTO, LMO/LTO, NMC/Graphite, andcapacitors, etc. For dual battery solutions, the architecture alsovaries from passive parallel connection to active switching. On theother hand, OEM are considering to leverage a lot more use out oftraditional 12V SLI (start, light, and ignition) for functions such aspower steering, air conditioning, heater, etc. Depending on batteryarchitecture and vehicle functioning design, the energy managementstrategy can easily become complicated.

Since many variables are involved in the design of 12V advanced startstop systems, an integrated simulation tool with a couple of modularizedmodels including vehicle, batteries, and performance characterizationhave been developed. The modularized tool would help to evaluate manyaspects of the design from motor size selection, power networkmanagement, battery evaluation, testing standardization. As a specificdemonstration, in this work, we use the tool to compare threechemistries: stand-alone AGM, stand-alone LFP, and dual batteries oflead acid and LTO for different driving cycles including NEDC, WLTP,FTP72, and HWFET as function of motor size.

References to relative positions (e.g., “top” and “bottom”) in thisdescription are merely used to identify various elements as are orientedin the Figures. Orientation of particular components may vary greatlydepending on the application in which they are used. For purposes ofthis disclosure, the term “coupled” means the joining of two membersdirectly or indirectly to one another. Such joining may be stationary innature or moveable in nature. Such joining may be achieved with the twomembers or the two members and any additional intermediate members beingintegrally formed as a single unitary body with one another or with thetwo members or the two members and any additional intermediate membersbeing attached to one another. Such joining may be permanent in natureor may be removable or releasable in nature. Construction andarrangement of the system, methods, and devices as shown in the variousexamples of embodiments is illustrative only. Although only a fewembodiments are described in detail in this disclosure, those skilled inthe art who review this disclosure will readily appreciate that manymodifications are possible (e.g., variations in sizes, dimensions,structures, shapes and proportions of the various elements, values ofparameters, mounting arrangements, use of materials, colors,orientations, etc.) without materially departing from the novelteachings and advantages of the subject matter recited. For example,elements shown as integrally formed may be constructed of multiple partsor elements shown as multiple parts may be integrally formed, theoperation of the interfaces may be reversed or otherwise varied, thelength or width of the structures and/or members or connector or otherelements of the system may be varied, the nature or number of adjustmentpositions provided between the elements may be varied (e.g. byvariations in the number of engagement slots or size of the engagementslots or type of engagement). The order or sequence of any algorithm,process, or method steps may be varied or re-sequenced according toalternative embodiments. Likewise, some algorithm or method stepsdescribed may be omitted, and/or other steps added. Other substitutions,modifications, changes and omissions may be made in the design,operating conditions and arrangement of the various examples ofembodiments without departing from the spirit or scope of the presentinventions.

While this invention has been described in conjunction with the examplesof embodiments outlined above, various alternatives, modifications,variations, improvements and/or substantial equivalents, whether knownor that are or may be presently foreseen, may become apparent to thosehaving at least ordinary skill in the art. Accordingly, the examples ofembodiments of the invention, as set forth above, are intended to beillustrative, not limiting. Various changes may be made withoutdeparting from the spirit or scope of the invention. Therefore, theinvention is intended to embrace all known or earlier developedalternatives, modifications, variations, improvements and/or substantialequivalents.

The technical effects and technical problems in the specification areexemplary and are not limiting. It should be noted that the embodimentsdescribed in the specification may have other technical effects and cansolve other technical problems. Aspects of the method described hereinare implemented on a software system running on a computer system. Tothis end, the methods and system may be implemented in, or inassociation with, a general-purpose software package or a specificpurpose software package. As a specific, non-limiting example, thedevice could be a battery tester in communication with a cloud storagedatabase and/or mobile device and/or a computer. As another specific,non-limiting example, the device could be a battery tester incommunication with a cloud storage database and/or mobile device and/oran OBD-II reader.

The software system described herein may include a mixture of differentsource codes. The system or method herein may be operated bycomputer-executable instructions, such as but not limited to, programmodules, executable on a computer. Examples of program modules include,but are not limited to, routines, programs, objects, components, datastructures, and the like which perform particular tasks or implementparticular instructions. The software system may also be operable forsupporting the transfer of information within a network.

While the descriptions may include specific devices or computers, itshould be understood the system and/or method may be implemented by anysuitable device (or devices) having suitable computational means. Thismay include programmable special purpose computers or general-purposecomputers that execute the system according to the relevantinstructions. The computer system or portable electronic device can bean embedded system, a personal computer, notebook computer, servercomputer, mainframe, networked computer, workstation, handheld computer,as well as now known or future developed mobile devices, such as forexample, a personal digital assistant, cell phone, smartphone, tabletcomputer, mobile scanning device, and the like. Other computer systemconfigurations are also contemplated for use with the communicationsystem including, but not limited to, multiprocessor systems,microprocessor-based or programmable electronics, network personalcomputers, minicomputers, smart watches, and the like. Preferably, thecomputing system chosen includes a processor suitable for efficientoperation of one or more of the various systems or functions orattributes of the communication system described.

The system or portions thereof may also be linked to a distributedcomputing environment, where tasks are performed by remote processingdevices that are linked through a communication network(s). To this end,the system may be configured or linked to multiple computers in anetwork including, but not limited to, a local area network, wide areanetwork, wireless network, and the Internet. Therefore, information,content, and data may be transferred within the network or system bywireless means, by hardwire connection, or combinations thereof.Accordingly, the devices described herein communicate according to nowknown or future developed pathways including, but not limited to, wired,wireless, and fiber-optic channels.

In one or more examples of embodiments, data may be stored remotely (andretrieved by the application) or may be stored locally on a user'sdevice in a suitable storage medium. Data storage may be in volatile ornon-volatile memory. Data may be stored in appropriate computer-readablemedium including read-only memory, random-access memory, CD-ROM, CD-R,CD-RW, magnetic tapes, flash drives, as well as other optical datastorage devices. Data may be stored and transmitted by and within thesystem in any suitable form. Any source code or other language suitablefor accomplishing the desired functions described herein may beacceptable for use.

Furthermore, the computer or computers or portable electronic devicesmay be operatively or functionally connected to one or more mass storagedevices, such as but not limited to, a hosted database or cloud-basedstorage. The system may also include computer-readable media which mayinclude any computer-readable media or medium that may be used to carryor store desired program code that may be accessed by a computer. Theinvention can also be embodied as computer-readable code on acomputer-readable medium. To this end, the computer-readable medium maybe any data storage device that can store data. The computer-readablemedium can also be distributed over a network-coupled computer system sothat the computer-readable code is stored and executed in a distributedfashion.

What is claimed is:
 1. A method of determining a battery solution for avehicle, the method comprising: developing a battery simulation module,the developing includes selecting a battery control strategy, whichincludes a battery charging strategy and a battery discharging strategy,and selecting a battery model; receiving a battery simulation inputgenerated as an output from a vehicle simulation module, the batterysimulation input includes a power profile based on a performancescenario applied to the vehicle simulation module, which has an enginesize and an electrical network for the vehicle; performing the batterysimulation including applying the battery simulation input to thebattery simulation model, and outputting performance characterizationsfor the battery simulation input; repeating the steps of developing abattery simulation module and performing the battery simulation with adifferent battery control strategy, a different battery model, or adifferent battery control strategy and a different battery model, therepeating the steps resulting in second performance characterizations;comparing the performance characterizations with the second performancecharacterizations; and selecting a battery solution based on thecomparison.
 2. The method of claim 1, wherein the battery solutionincludes a battery chemistry and a battery size.
 3. The method of claim1, and further comprising: developing the vehicle simulation module withthe performance scenario, the developing includes selecting a vehiclehaving a theoretically infinite battery; receiving a driving profileinput; and performing the vehicle simulation including applying thedriving profile input to the vehicle simulation module, and outputting apower profile.
 4. The method of claim 3, wherein the driving profileinput includes a driving profile for an advanced start-stop vehicle. 5.The method of claim 1, wherein developing the vehicle simulation moduleincludes selecting an electrical network for the vehicle by selectingloads and management for the loads.
 6. The method of claim 1, whereinthe battery model includes a battery chemistry, a battery architecture,and a battery parameter.
 7. The method of claim 1, wherein the powerprofile includes a vehicle state and a power request.
 8. The method ofclaim 1, wherein the performance characterizations includes aperformance characterization selected from the group consisting of fueleconomy, charge acceptance, State of Charge (SoC) swing, ampere hour(Ah) throughput, and peak power.
 9. A method of determining a batterysolution for a class of vehicles, the method comprising: developing avehicle simulation module, the developing includes selecting a class ofvehicles having a theoretically infinite battery, an engine size, and anelectrical network; receiving a driving profile input; performing thevehicle simulation including applying the driving profile input to thevehicle simulation module, and outputting a power profile being relatedto the battery simulation input; developing a battery simulation module,the developing includes selecting a battery control strategy, whichincludes a battery charging strategy and battery discharging strategy,and selecting a battery model; receiving a battery simulation inputgenerated as the output from the vehicle simulation module, the batterysimulation input includes a power profile; performing the batterysimulation including applying the battery simulation input to thebattery simulation model, and outputting performance characterizationsfor the battery simulation input; repeating the steps of developing abattery simulation module and performing the battery simulation with adifferent battery control strategy, a different battery model, or adifferent battery control strategy and a different battery model, therepeating the steps resulting in second performance characterizations;comparing the performance characterizations with the second performancecharacterizations; and selecting a battery solution based on thecomparison, the battery solution including a battery chemistry and abattery size.
 10. The method of claim 9, wherein the battery modelincludes a battery chemistry, a battery architecture, and a batteryparameter.
 11. The method of claim 9, wherein the performancecharacterizations includes a performance characterization selected fromthe group consisting of fuel economy, charge acceptance, State of Charge(SoC) swing, ampere hour (Ah) throughput, and peak power.
 12. The methodof claim 9, wherein selecting an electrical network for the class ofvehicles includes selecting loads and management for the loads.
 13. Themethod of claim 9, wherein the driving profile input includes a drivingprofile for an advanced start-stop vehicle.